MCMC from Scratch: A Practical Introduction to Markov Chain Monte Carlo
Description
MCMC from Scratch: A Practical Introduction to Markov Chain Monte Carlo By Hanada, Masanori Published by Springer Publication Date: 2022-10-21 Subject: Computers Artificial Intelligence General, Computers Programming Algorithms, Computers Artificial Intelligence - General, Computers Programming - Algorithms, Mathematics Probability & Statistics General, Mathematics Probability & Statistics - General, Science Life Sciences Biophysics, Science Physics Nuclear, Science Life Sciences - Biophysics, Science Physics - Nuclear, Biophysics, Machine Learning, Numerical Analysis, Particle & High-Energy Physics, Probability & Statistics, Algorithms And Data Structures, Particle And High-Energy Physics, Probability And Statistics, Numerical Analysis, Probability & Statistics, Machine Learning, Particle & High-Energy Physics, Biophysics, Computers Programming Algorithms, Computers, Programming, Algorithms, Mathematics Probability & Statistics General, Mathematics, Probability & Statistics, General, Computers Artificial Intelligence General, Artificial Intelligence, Science Physics Nuclear, Science, Physics, Nuclear, Science Life Sciences Biophysics, Life Sciences, Algorithms And Data Structures, Probability And Statistics, Particle And High-Energy Physics, Markov Processes, Monte Carlo Method, Anf: Computers And It Subject Keywords: Markov Chain Monte Carlo; MCMC; Numerical simulation; Computational science; Metropolis algorithm; HMC algorithm; Gibbs Sampling algorithm; Metropolis-Hastings algorithm; Replica exchange algorithm Genre: Numerical Analysis, Probability & Statistics, Machine Learning, Particle & High-Energy Physics, Biophysics, Computers, Programming, Algorithms, Mathematics, Probability & Statistics, General, Computers, Artificial Intelligence, General, Science, Physics, Nuclear, Science, Life Sciences, Biophysics, Algorithms And Data Structures, Probability And Statistics, Machine Learning, Particle And High-Energy Physics, Biophysics Target Audience: Professional and scholarly
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